Detect code smells, security vulnerabilities, anomalies, and trends across codebases using regex, AST analysis, and statistical methods.

• Identifies problematic patterns including long functions, duplicate code, magic numbers, empty catch blocks, and TODO/FIXME markers
• Scans for security risks such as SQL injection, hard-coded secrets, dangerous function usage (eval, innerHTML), and credential exposure patterns
• Performs statistical anomaly detection using Z-score and IQR methods to flag outliers in numerical data
• Includes regex-based sensitive data detection for emails, phone numbers, credit cards, and SSNs, plus time-series trend analysis with moving averages and growth rate calculation
• Generates structured reports with severity levels and actionable recommendations; read-only operation with built-in false-positive awareness